Many scientific, engineering, medical, and other technologies seek to detect the presence of an object within a medium. For example, some technologies detect the presence of (i) buried land mines in a roadway or a field for military or humanitarian purposes, or (ii) potentially hidden explosives placed aboveground hidden among man-made clutter. Such technologies may use ultra wideband penetrating radar technologies, such as ground-penetrating radar (“GPR”) antennas that are mounted on the front of a vehicle that travels down a track (e.g., a roadway or across a field). The antennas could be directed into the ground with the soil being the medium and the top of the soil or pavement being the surface. In this case, GPR systems can be used to detect not only metallic objects but also nonmetallic objects whose dielectric properties are sufficiently different from those of the soil. When a radar signal strikes a subsurface object, it is reflected back as a return signal to a receiver. Current GPR systems typically analyze the strength or amplitude of the return signals directly to identify the presence of the object. Some GPR systems may, however, generate tomography images from the return signals. In the medical field, computer-assisted tomography uses X-rays to generate tomography images for detecting the presence of abnormalities (i.e., subsurface objects) within a body. In the engineering field, GPR systems have been designed to generate spatial images of underground areas, as well as those aboveground, that may contain potentially hidden explosives, or the interior of concrete structures such as bridges, dams, and containment vessels in order to assess the integrity of the structures. In such images, the objects of interest tend to appear as distinct bright spots. In addition to referring to a foreign object that is within a medium, the term “object” also refers to any characteristic of the medium (e.g., a crack in the medium or a change in the medium's density) that is to be detected.
Some current technologies seek to detect the presence of new objects that were not detected in previous passes. For example, a convoy of military vehicles may travel over a certain roadway fairly often. If access to the roadway is not tightly controlled, the military may need to check, each time a convoy is to travel down the roadway, for the presence of land mines or other objects that may pose a hazard. As another example, a civil engineering firm may check bridges, dams, and other structures on a regular basis (e.g., yearly) for the presence of new subsurface defects (e.g., cracks). Each time the structure, roadway, or area is scanned, large amounts of data may be collected and processed. For example, the scan of the roadway may collect GPR return signals every few centimeters. GPR systems may generate image frames from the return signals and detect subsurface objects in those image frames. Successive scans of a structure or roadway will often be translationally misaligned due to GPS navigation errors. When GPR systems have access to data from previous scans of a structure or roadway, the GPR systems may detect change by (i) spatially registering misaligned images or other 2D rasters of data derived from GPR return signals on the current scan to images or other 2D rasters from previous scans, and (ii) comparing the co-registered images or rasters. This approach requires a potentially large database of images or rasters derived from GPR return signals acquired on previous scans.
Current operational penetrating radar systems do not use the results from previous scans to perform change detection for objects in real-time. A major hurdle in achieving this goal is that the cost of storing the vast amounts of data collected from previous scans and comparing data from those previous scans to the latest scan may be very high. A real-time system needs to process the return signals from successive sampling locations of the vehicle as it proceeds down track so that, in the steady state, the return signals for one sampling location are processed within the time between samplings. Moreover, in the case of a vehicle that detects land mines, a real-time system may need to detect the presence of the land mine in time to stop the vehicle before it reaches the land mine.